



'''simple docstring'''

import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
			from PIL import Image

			from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor

@require_vision
class 							a__( unittest.TestCase     ):






			def 						_lowercase  (     self						)							->							List[str]:
					snake_case__	     =tempfile.mkdtemp()

					snake_case__	     =[
					    '[UNK]',
					    '[CLS]',
					    '[SEP]',
					    '[PAD]',
					    '[MASK]',
					    '的',
					    '价',
					    '格',
					    '是',
					    '15',
					    '便',
					    'alex',
					    '##andra',
					    '，',
					    '。',
					    '-',
					    't',
					    'shirt',
					]
					snake_case__	     =os.path.join(self.tmpdirname					,   VOCAB_FILES_NAMES['vocab_file']						)
					with open(self.vocab_file					,   'w'					,   encoding='utf-8'						) as vocab_writer:
							vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]						)						)

					snake_case__	     ={
					    'do_resize': True,
					    'size': {'height': 224, 'width': 224},
					    'do_center_crop': True,
					    'crop_size': {'height': 18, 'width': 18},
					    'do_normalize': True,
					    'image_mean': [0.48_145_466, 0.4_578_275, 0.40_821_073],
					    'image_std': [0.26_862_954, 0.26_130_258, 0.27_577_711],
					    'do_convert_rgb': True,
					}
					snake_case__	     =os.path.join(self.tmpdirname					,   _UpperCAmelCase						)
					with open(self.image_processor_file					,   'w'					,   encoding='utf-8'						) as fp:
							json.dump(_UpperCAmelCase					,   _UpperCAmelCase						)






			def 						_lowercase  (     self					,   **_UpperCAmelCase						)							->							str:
					return BertTokenizer.from_pretrained(self.tmpdirname					,   **_UpperCAmelCase						)






			def 						_lowercase  (     self					,   **_UpperCAmelCase						)							->							List[str]:
					return BertTokenizerFast.from_pretrained(self.tmpdirname					,   **_UpperCAmelCase						)






			def 						_lowercase  (     self					,   **_UpperCAmelCase						)							->							Tuple:
					return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname					,   **_UpperCAmelCase						)






			def 						_lowercase  (     self						)							->							List[Any]:
					shutil.rmtree(self.tmpdirname						)






			def 						_lowercase  (     self						)							->							Optional[Any]:
					snake_case__	     =[np.random.randint(255					,   size=(3, 30, 400)					,   dtype=np.uinta						)]

					snake_case__	     =[Image.fromarray(np.moveaxis(_UpperCAmelCase					,   0					,   -1						)						) for x in image_inputs]

					return image_inputs






			def 						_lowercase  (     self						)							->							Union[str, Any]:
					snake_case__	     =self.get_tokenizer()
					snake_case__	     =self.get_rust_tokenizer()
					snake_case__	     =self.get_image_processor()

					snake_case__	     =ChineseCLIPProcessor(tokenizer=_UpperCAmelCase					,   image_processor=_UpperCAmelCase						)
					processor_slow.save_pretrained(self.tmpdirname						)
					snake_case__	     =ChineseCLIPProcessor.from_pretrained(self.tmpdirname					,   use_fast=_UpperCAmelCase						)

					snake_case__	     =ChineseCLIPProcessor(tokenizer=_UpperCAmelCase					,   image_processor=_UpperCAmelCase						)
					processor_fast.save_pretrained(self.tmpdirname						)
					snake_case__	     =ChineseCLIPProcessor.from_pretrained(self.tmpdirname						)

					self.assertEqual(processor_slow.tokenizer.get_vocab()					,   tokenizer_slow.get_vocab()						)
					self.assertEqual(processor_fast.tokenizer.get_vocab()					,   tokenizer_fast.get_vocab()						)
					self.assertEqual(tokenizer_slow.get_vocab()					,   tokenizer_fast.get_vocab()						)
					self.assertIsInstance(processor_slow.tokenizer					,   _UpperCAmelCase						)
					self.assertIsInstance(processor_fast.tokenizer					,   _UpperCAmelCase						)

					self.assertEqual(processor_slow.image_processor.to_json_string()					,   image_processor.to_json_string()						)
					self.assertEqual(processor_fast.image_processor.to_json_string()					,   image_processor.to_json_string()						)
					self.assertIsInstance(processor_slow.image_processor					,   _UpperCAmelCase						)
					self.assertIsInstance(processor_fast.image_processor					,   _UpperCAmelCase						)






			def 						_lowercase  (     self						)							->							int:
					snake_case__	     =ChineseCLIPProcessor(tokenizer=self.get_tokenizer()					,   image_processor=self.get_image_processor()						)
					processor.save_pretrained(self.tmpdirname						)

					snake_case__	     =self.get_tokenizer(cls_token='(CLS)'					,   sep_token='(SEP)'						)
					snake_case__	     =self.get_image_processor(do_normalize=_UpperCAmelCase						)

					snake_case__	     =ChineseCLIPProcessor.from_pretrained(
					    self.tmpdirname					,   cls_token='(CLS)'					,   sep_token='(SEP)'					,   do_normalize=_UpperCAmelCase						)

					self.assertEqual(processor.tokenizer.get_vocab()					,   tokenizer_add_kwargs.get_vocab()						)
					self.assertIsInstance(processor.tokenizer					,   _UpperCAmelCase						)

					self.assertEqual(processor.image_processor.to_json_string()					,   image_processor_add_kwargs.to_json_string()						)
					self.assertIsInstance(processor.image_processor					,   _UpperCAmelCase						)






			def 						_lowercase  (     self						)							->							Optional[Any]:
					snake_case__	     =self.get_image_processor()
					snake_case__	     =self.get_tokenizer()

					snake_case__	     =ChineseCLIPProcessor(tokenizer=_UpperCAmelCase					,   image_processor=_UpperCAmelCase						)

					snake_case__	     =self.prepare_image_inputs()

					snake_case__	     =image_processor(_UpperCAmelCase					,   return_tensors='np'						)
					snake_case__	     =processor(images=_UpperCAmelCase					,   return_tensors='np'						)

					for key in input_feat_extract.keys():
							self.assertAlmostEqual(input_feat_extract[key].sum()					,   input_processor[key].sum()					,   delta=1E-2						)






			def 						_lowercase  (     self						)							->							Dict:
					snake_case__	     =self.get_image_processor()
					snake_case__	     =self.get_tokenizer()

					snake_case__	     =ChineseCLIPProcessor(tokenizer=_UpperCAmelCase					,   image_processor=_UpperCAmelCase						)

					snake_case__	     ='Alexandra，T-shirt的价格是15便士。'

					snake_case__	     =processor(text=_UpperCAmelCase						)

					snake_case__	     =tokenizer(_UpperCAmelCase						)

					for key in encoded_tok.keys():
							self.assertListEqual(encoded_tok[key]					,   encoded_processor[key]						)






			def 						_lowercase  (     self						)							->							Dict:
					snake_case__	     =self.get_image_processor()
					snake_case__	     =self.get_tokenizer()

					snake_case__	     =ChineseCLIPProcessor(tokenizer=_UpperCAmelCase					,   image_processor=_UpperCAmelCase						)

					snake_case__	     ='Alexandra，T-shirt的价格是15便士。'
					snake_case__	     =self.prepare_image_inputs()

					snake_case__	     =processor(text=_UpperCAmelCase					,   images=_UpperCAmelCase						)

					self.assertListEqual(list(inputs.keys()						)					,   ['input_ids', 'token_type_ids', 'attention_mask', 'pixel_values']						)

					# test if it raises when no input is passed
					with pytest.raises(_UpperCAmelCase						):
							processor()






			def 						_lowercase  (     self						)							->							str:
					snake_case__	     =self.get_image_processor()
					snake_case__	     =self.get_tokenizer()

					snake_case__	     =ChineseCLIPProcessor(tokenizer=_UpperCAmelCase					,   image_processor=_UpperCAmelCase						)

					snake_case__	     =[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

					snake_case__	     =processor.batch_decode(_UpperCAmelCase						)
					snake_case__	     =tokenizer.batch_decode(_UpperCAmelCase						)

					self.assertListEqual(_UpperCAmelCase					,   _UpperCAmelCase						)






			def 						_lowercase  (     self						)							->							int:
					snake_case__	     =self.get_image_processor()
					snake_case__	     =self.get_tokenizer()

					snake_case__	     =ChineseCLIPProcessor(tokenizer=_UpperCAmelCase					,   image_processor=_UpperCAmelCase						)

					snake_case__	     ='Alexandra，T-shirt的价格是15便士。'
					snake_case__	     =self.prepare_image_inputs()

					snake_case__	     =processor(text=_UpperCAmelCase					,   images=_UpperCAmelCase						)

					self.assertListEqual(list(inputs.keys()						)					,   processor.model_input_names						)









'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import _LazyModule


SCREAMING_SNAKE_CASE__     :						Dict	=  {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}


if TYPE_CHECKING:
			from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
			import sys

			SCREAMING_SNAKE_CASE__     :						Dict	=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




